The Association Between Afghan Refugees’ Food Insecurity and Socio-economic Factors in Iran: A Case Study of Khorasan Razavi Province
Bibliographic record
Abstract
Afghan refugees are one of the most vulnerable migrant groups in terms of food insecurity status around the world. We aimed to investigate the association between Afghan protracted refugees' food insecurity and its socio– economic determinants in Mashhad, Iran. In a cross– sectional design, information was gathered through face– to– face interviews with 299 Afghan main income earners or his/her representative in Golshar district, Mashhad, Iran. In a quantitative approach, the association of socio– economic factors with food insecurity was assessed. The results showed that less than 1% of all the households were food secure, 69.2% of those with children and 47.5% of those with no child faced severe food insecurity. Class of households' income, residency status and personal dwelling were significantly associated with severe food insecurity of Afghan refugees. Determining effective socio– economic factors to formulate appropriate policies and practices is not only necessary but also inevitable to assure sustainable food security for refugees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".